Equally remarkable is the method by which this information came to light. The study, led by The Nature Conservancy, with support from JetBlue, the World Travel & Tourism Council and Microsoft, merged contemporary culture with modern science by using artificial intelligence to analyze social media content. Social media platforms provide valuable insight into how the general public spends their recreational time and, importantly, their discretionary income. Machine-learning algorithms, a type of artificial intelligence, allow computers to autonomously make determinations based on learned information.
Using algorithms developed by the Microsoft Cognitive Services Computer Vision API, the study analyzed over 86,000 social images and nearly 6.7 million social text posts for visual and language identifiers that indicated reef-adjacent activities, such as white beaches, turquoise waters, reef fish and sea turtles, which were then selected according to geotags indicating proximity to a reef of 30 kilometers or less. The social media metrics derived using artificial intelligence were integrated with traditionally sourced data, like visitor center surveys, tourism business sales figures and government-reported economic data, to produce estimated reef-adjacent economic values for 32 Caribbean countries and territories.